1. Field of the Invention
The present invention is directed to a method and apparatus for generating an image for display from medical image data of a subject.
2. Description of the Prior Art
In the medical imaging field, several imaging schemes are known. For example PET (Positron Emission Tomography) is a method for imaging a subject in 3D using an injected radio-active substance which is processed in the body, typically resulting in an image indicating one or more biological functions.
A key criterion used in evaluating suspicious lesions in a PET scan is the Standardized Uptake Value (SUV). This value is computed from the number of counts of emission events recorded per voxel in the image reconstructed from the event data captured in the PET scan (coincidence emission events along the line of response). Effectively the SUV's purpose is to provide a standardized measure of the spatial distribution of radiotracer concentration throughout the imaged portion of the body.
Partial volume effect (PVE) in PET is due to a combination of the finite spatial resolution of the scanner and image sampling. It results in under-estimation of the true activity for small lesions (or any hot region against a cold background). The effect is typically apparent for lesions smaller than three times the full width at half maximum (FWHM) of the reconstructed image resolution.
The magnitude of this effect on mean SUV for a typical PET scanner is shown in the table below (Table 1), where the recovery coefficient is the percentage of the true lesion-to-background ratio measured in the reconstructed image. The table lists typical recovery coefficients for spherical lesions with a 4:1 lesion-to-background activity concentration ratio. These values were obtained from a NEMA Image Quality phantom scanned on a Siemens Biograph Scanner and reconstructed using OSEM with a 5 mm FWHM post filter.
TABLE 1Lesion diameterRecovery coefficient10 mm22.5%13 mm39.4%17 mm55.1%22 mm71.7%
While no approach to partial volume correction (PVC) is currently available clinically, a number of approaches have been proposed. Soret et al. ((2007) Partial volume effect in PET tumor imaging, JNM. 48(6); 932-944.) provides a comprehensive review of these methods. In brief, these methods can be broadly classified into three groups:
1. Those using anatomical information from higher resolution imaging modalities to correct for spill-over and tissue-fraction effects (e.g., the GTM method by Rousset et al. ((1998) Correction for partial volume effects in PET: principle and validation, JNM. 39; 904-9111998));
2. Those using iterative deconvolution to correct for the point spread function (PSF) of the system (e.g., Teo et al. ((2007) Partial volume correction in PET: validation of an iterative post reconstruction method with phantom and patient data, JNM. 48; 802-810));
3. Those using predetermined recovery coefficients as measured from phantom acquisitions (e.g., in the form of a look up table).
With the exception of one approach by Baete et al. ((2004) Evaluation of anatomy based reconstruction for partial volume correction in brain FDG-PET, NeuroImage. 23; 305-317), which falls into the first group above, each of these methods takes the fully reconstructed image as input.
Methods from groups 1 and 3 require significant user input prior to correction of PVE, and are heavily dependent on the quality of the segmentation and registration necessary for performing the correction.
Methods from group 2 require little user intervention on top of the usual definition of the region of interest (ROI) for quantification. However, they require an accurate approximation of the PSF of the system.